Meeting Title: LMNT Stand Up Date: 2026-04-20 Meeting participants: Jasmin Multani, Garrett Gibson, Advait Nandakumar Menon, Greg Stoutenburg, Awaish Kumar
WEBVTT
1 00:00:17.900 ⇒ 00:00:19.320 Garrett Gibson: Hey guys, can you hear me?
2 00:00:20.650 ⇒ 00:00:22.310 Jasmin Multani: Second year.
3 00:00:22.310 ⇒ 00:00:22.700 Advait Nandakumar Menon: Yay.
4 00:00:22.700 ⇒ 00:00:25.109 Garrett Gibson: Okay. Hey, guys. Hey, Adam.
5 00:00:34.450 ⇒ 00:00:38.270 Garrett Gibson: I think, we’re waiting for anyone else here today?
6 00:00:38.500 ⇒ 00:00:40.329 Garrett Gibson: A wish, maybe? Yeah.
7 00:00:40.940 ⇒ 00:00:44.410 Jasmin Multani: I need them for some context on our…
8 00:00:44.750 ⇒ 00:00:46.450 Garrett Gibson: Bottling, right? Yeah.
9 00:01:04.140 ⇒ 00:01:06.229 Jasmin Multani: I just messaged him right now.
10 00:01:10.340 ⇒ 00:01:12.960 Garrett Gibson: Did you get a chance to go through the slides of it?
11 00:01:16.720 ⇒ 00:01:19.320 Advait Nandakumar Menon: Nope, not yet.
12 00:01:21.850 ⇒ 00:01:23.169 Jasmin Multani: The sides look great.
13 00:01:23.520 ⇒ 00:01:33.919 Jasmin Multani: Like, a lot more, I feel like they’re more precise, and the language is, like, I can understand which… I can understand which milestone it’s talking about.
14 00:01:33.920 ⇒ 00:01:40.220 Garrett Gibson: Yeah, I did a bunch more iterations, and yeah, as I mentioned, I created the two new slides to tie to her, like.
15 00:01:40.750 ⇒ 00:01:45.370 Garrett Gibson: spreadsheets, I think that’s a lot cleaner than the… just relying on linear and,
16 00:01:46.300 ⇒ 00:01:50.039 Garrett Gibson: What else? I can’t even think of what else.
17 00:01:50.550 ⇒ 00:01:51.300 Garrett Gibson: Yes.
18 00:01:51.300 ⇒ 00:01:52.080 Jasmin Multani: Accelerator.
19 00:01:52.080 ⇒ 00:01:54.220 Garrett Gibson: Yeah, exactly.
20 00:01:54.530 ⇒ 00:01:59.990 Jasmin Multani: Okay, cool, cool, cool. So, I can kick off this meeting now that everyone’s here.
21 00:02:00.380 ⇒ 00:02:03.769 Jasmin Multani: And we can start off with the linear tickets.
22 00:02:04.360 ⇒ 00:02:10.080 Jasmin Multani: So, just as an FYI for the rest of the team, given that Shivani’s
23 00:02:10.600 ⇒ 00:02:27.059 Jasmin Multani: been very strict about not using pilot com… pilot and expansion language. We’re gonna, Greg and I have aligned that we’re gonna re-scope some of the linear project milestones, to be, like, deliverable-focused, like.
24 00:02:27.400 ⇒ 00:02:37.159 Jasmin Multani: function, team-wise. So, their internal team has an e-commerce, their internal team has supply chain, and they’re separate, dashboards, and…
25 00:02:37.270 ⇒ 00:02:51.550 Jasmin Multani: different levels of effort, that will go in for each dashboard. So, instead of saying omni expansion, I’m just gonna be, like, supply chain or, e-commerce and so forth.
26 00:02:51.720 ⇒ 00:02:56.809 Jasmin Multani: So just to be on the lookout for there, I feel like it’ll be a lot cleaner.
27 00:02:56.990 ⇒ 00:02:59.110 Jasmin Multani: To estimate turnaround time.
28 00:03:00.210 ⇒ 00:03:03.200 Jasmin Multani: Also, one call-out…
29 00:03:03.670 ⇒ 00:03:16.849 Jasmin Multani: Shivani’s gonna be gone the last week of May and the first week of June, so if we can… so that… that May 22nd,
30 00:03:17.020 ⇒ 00:03:21.649 Jasmin Multani: deadline that she’s given us, that’s, like, the upper limit.
31 00:03:22.250 ⇒ 00:03:28.350 Jasmin Multani: she, for sure, is just… when she’s out of office, she’s not… I doubt she’s gonna be checking her phone.
32 00:03:28.610 ⇒ 00:03:33.049 Jasmin Multani: So let’s try to… we can try to, like, aim for that.
33 00:03:33.260 ⇒ 00:03:34.360 Jasmin Multani: time period.
34 00:03:35.420 ⇒ 00:03:49.269 Jasmin Multani: And then from there… I also… had… created this internal business review.
35 00:03:49.530 ⇒ 00:03:58.500 Jasmin Multani: This, this… Okay, well, that’ll be on… be on the lookout for that from… Garrett, but ideally.
36 00:03:58.830 ⇒ 00:04:07.250 Jasmin Multani: I wanted to make that business review something that’s internal, so that we can all, chime in and say, hey, this is the blocker, this is the risk.
37 00:04:07.330 ⇒ 00:04:20.450 Jasmin Multani: And we can be a bit more candid about where we’re at versus the slide deck, which is more client-focused. And, we’re limited in what we were really showing.
38 00:04:20.720 ⇒ 00:04:31.380 Jasmin Multani: Ideally, I do feel like everyone should chime in, rather than, like, rely on Garrett to, like, run, run things, like.
39 00:04:32.440 ⇒ 00:04:35.450 Jasmin Multani: Run an assessment of the linear tickets.
40 00:04:35.630 ⇒ 00:04:54.069 Jasmin Multani: I’m hoping that weekly business review is gonna be more honest from each of us, being like, hey, this is on track, or like, hey, this is, like, a budding net new project that is not found in Linear or any of our contracts right now.
41 00:04:54.740 ⇒ 00:05:00.769 Jasmin Multani: Recording this here in this document so that other people can take a look and, like, give first impressions.
42 00:05:01.150 ⇒ 00:05:14.380 Jasmin Multani: So, ideally, it’s not supposed to be more homework, but it should only take 5 minutes to fill out, every Tuesday, and I do feel like each person should be, driving the notes on their own.
43 00:05:16.320 ⇒ 00:05:17.460 Jasmin Multani: Okay, cool.
44 00:05:17.620 ⇒ 00:05:27.079 Jasmin Multani: Alright, let me go into issues, and just like last time, I’m gonna go person by person, and do, like, a pulse check.
45 00:05:28.330 ⇒ 00:05:34.099 Jasmin Multani: So, Avid… Your name is first, because… Name starts with an A.
46 00:05:35.270 ⇒ 00:05:44.700 Advait Nandakumar Menon: Yeah, so, from my side, both of us were working on the first feedback for the retail dashboard, yeah, the geography one.
47 00:05:44.790 ⇒ 00:05:49.279 Advait Nandakumar Menon: So, a couple of things have… most of the things I have knocked out on it.
48 00:05:49.360 ⇒ 00:06:05.670 Advait Nandakumar Menon: The only pending thing is the capitalization, which I have to do a change in the topic, which I’ll be doing along with the, point-of-sale expansion as well across the topic and AI context. So, I’ve created another ticket for that.
49 00:06:05.670 ⇒ 00:06:06.150 Jasmin Multani: Oh, no.
50 00:06:06.150 ⇒ 00:06:08.550 Advait Nandakumar Menon: Yeah. Yeah.
51 00:06:08.810 ⇒ 00:06:17.930 Advait Nandakumar Menon: I think it’s 369 and 370, so I’ll be focusing on those two first before proceeding with the other feedback tickets you have created just now.
52 00:06:18.680 ⇒ 00:06:21.130 Jasmin Multani: Okay, yeah. So, yeah, this…
53 00:06:21.330 ⇒ 00:06:27.509 Jasmin Multani: Align with that, do these first, because, they’re the basis of those other dashboards.
54 00:06:27.610 ⇒ 00:06:37.030 Jasmin Multani: And then, once you ping me, I can give… because Shivani gave an estimate of, like, give me a dashboard a day to review.
55 00:06:39.240 ⇒ 00:06:46.959 Jasmin Multani: we’ll give this for her to bite into while you churn out the other dashboard so that we have some time on the back.
56 00:06:47.290 ⇒ 00:06:48.480 Jasmin Multani: Yeah.
57 00:06:49.300 ⇒ 00:06:52.510 Jasmin Multani: Yeah, so sounds good, like, feel aligned about…
58 00:06:53.030 ⇒ 00:06:57.089 Jasmin Multani: Doing those ones first. 369 and 370, cool.
59 00:06:57.340 ⇒ 00:07:03.000 Jasmin Multani: Can you talk about what this… these two are?
60 00:07:04.870 ⇒ 00:07:05.409 Jasmin Multani: These are…
61 00:07:05.410 ⇒ 00:07:06.380 Advait Nandakumar Menon: So, those…
62 00:07:06.500 ⇒ 00:07:13.879 Advait Nandakumar Menon: Yeah, those were created from before I came, and I think it was assigned to me, so even I’m not quite sure…
63 00:07:14.440 ⇒ 00:07:17.219 Advait Nandakumar Menon: What the scope is over there.
64 00:07:17.730 ⇒ 00:07:31.170 Jasmin Multani: Okay, I think maybe with them cut these, so let me chat with him once… once… once Robert and with them are back from their event, I can, like, hey, these tickets were… because they’re…
65 00:07:31.170 ⇒ 00:07:42.820 Jasmin Multani: the… I see a similar issue on Eden, where I have tickets, and I’m like, I have no context of this. Is this outdated? Yes or no? So I’m doing cleanup there, and I can look there.
66 00:07:43.090 ⇒ 00:07:44.140 Jasmin Multani: Google. Sure.
67 00:07:44.620 ⇒ 00:07:51.050 Jasmin Multani: And just as an FYI for the rest of the team, Shivani has asked for a net new sales dashboard.
68 00:07:51.470 ⇒ 00:07:56.559 Jasmin Multani: one for wholesale version, and one for retail. This is…
69 00:07:56.720 ⇒ 00:08:03.420 Jasmin Multani: Because we’ve already given her 5 dashboards already, this is…
70 00:08:04.480 ⇒ 00:08:08.659 Jasmin Multani: this is beyond our promise, so I’m gonna, chat with…
71 00:08:09.230 ⇒ 00:08:13.270 Jasmin Multani: Robert before having Avid commit to this.
72 00:08:13.550 ⇒ 00:08:18.560 Jasmin Multani: To be like, hey… This is, like, a…
73 00:08:18.880 ⇒ 00:08:23.979 Jasmin Multani: a rabbit hole. Maybe we should just, like, keep this as, like, a simple…
74 00:08:24.320 ⇒ 00:08:31.040 Jasmin Multani: sheet, like, omni sheet, if it takes, like, 30 minutes to make. But…
75 00:08:31.400 ⇒ 00:08:34.739 Jasmin Multani: We’ll discuss there before you start working on it.
76 00:08:35.159 ⇒ 00:08:43.409 Jasmin Multani: One other call-out for the rest of the team is I’m having Avid work on sheets.
77 00:08:44.150 ⇒ 00:08:45.709 Jasmin Multani: I think in the…
78 00:08:45.920 ⇒ 00:08:46.940 Advait Nandakumar Menon: Exeter part of this one.
79 00:08:46.940 ⇒ 00:08:52.680 Jasmin Multani: Yeah, yeah, yeah. So, we’re gonna test run a, you know,
80 00:08:52.790 ⇒ 00:09:00.340 Jasmin Multani: how long does it take for an analyst to roll off information from Google Sheets to OmniSheets?
81 00:09:00.490 ⇒ 00:09:08.919 Jasmin Multani: And B, can… are we able to link information from the OmniSheets directly onto the Omni dashboard?
82 00:09:09.260 ⇒ 00:09:27.879 Jasmin Multani: And if this looks good, and it seems like an easy lift, we will replicate across all dashboards moving forward. If it’s too big of a lift, then we’ll have to, like, figure out whether it’s easier to do just the usual SQL-based, tables.
83 00:09:29.510 ⇒ 00:09:30.810 Jasmin Multani: Okay, cool, cool, cool.
84 00:09:31.090 ⇒ 00:09:32.830 Jasmin Multani: Any other questions?
85 00:09:35.130 ⇒ 00:09:35.920 Jasmin Multani: If not…
86 00:09:35.920 ⇒ 00:09:37.030 Advait Nandakumar Menon: Nothing from it.
87 00:09:37.620 ⇒ 00:09:38.420 Jasmin Multani: Okay, okay.
88 00:09:38.950 ⇒ 00:09:40.859 Jasmin Multani: Let me move on to a wish.
89 00:09:43.640 ⇒ 00:09:44.950 Jasmin Multani: Okay, I wish.
90 00:09:45.270 ⇒ 00:09:50.120 Jasmin Multani: Are there any updates that you want to give us for e-commerce or modeling?
91 00:09:53.120 ⇒ 00:09:53.960 Jasmin Multani: I think you’re on mute.
92 00:09:53.960 ⇒ 00:09:59.789 Awaish Kumar: Yes, so we… Yeah, for,
93 00:10:00.380 ⇒ 00:10:09.200 Awaish Kumar: Amazon, Walmart, Espin’s API, I don’t have any updates from UTAM or other element team regarding injections, but,
94 00:10:09.380 ⇒ 00:10:13.030 Awaish Kumar: I’ve started rolling MECOM with whatever data I have.
95 00:10:13.300 ⇒ 00:10:18.299 Awaish Kumar: I have some data from Shopify, and then we have data from Amazon.
96 00:10:18.880 ⇒ 00:10:20.689 Awaish Kumar: I have shared my…
97 00:10:20.850 ⇒ 00:10:29.360 Awaish Kumar: findings in the Slack channel last week regarding, Amazon modeling. So, model is ready, but there are some,
98 00:10:31.290 ⇒ 00:10:36.520 Awaish Kumar: Issues with how we are able to get some pricing information.
99 00:10:37.580 ⇒ 00:10:40.539 Awaish Kumar: And I have raised their… I have tagged you, I think.
100 00:10:40.660 ⇒ 00:10:46.800 Awaish Kumar: that I will need help from a strategy team to… But… and the…
101 00:10:47.580 ⇒ 00:10:49.989 Awaish Kumar: and the QA there, and then…
102 00:10:50.620 ⇒ 00:10:55.430 Awaish Kumar: Come up with a final, modeling… requirements.
103 00:10:55.580 ⇒ 00:11:05.990 Awaish Kumar: For order item tables. So, thing is that the connector that we are using for Amazon does not give us data in a
104 00:11:06.170 ⇒ 00:11:08.169 Awaish Kumar: Format we expect.
105 00:11:08.490 ⇒ 00:11:13.109 Awaish Kumar: So, I’m trying to grab the data from a few different tables.
106 00:11:13.460 ⇒ 00:11:22.469 Awaish Kumar: there is, like, financial events, and… which have, refunds, and then maybe you have sales data, and I’m trying to…
107 00:11:22.710 ⇒ 00:11:31.389 Awaish Kumar: bring that in, so I can figure out, for each order, or the line item, what is the revenue discount, fees.
108 00:11:31.510 ⇒ 00:11:32.680 Awaish Kumar: everything.
109 00:11:32.990 ⇒ 00:11:34.599 Awaish Kumar: So, I have…
110 00:11:35.230 ⇒ 00:11:41.899 Awaish Kumar: models that… that bring the data into the snowflake. What I need from the strategy team is
111 00:11:42.200 ⇒ 00:11:44.530 Awaish Kumar: to QA that with the…
112 00:11:45.270 ⇒ 00:11:48.309 Awaish Kumar: With the platform itself, to…
113 00:11:48.900 ⇒ 00:11:54.680 Awaish Kumar: So we can say, like, if an order is showing the number is the same, is it…
114 00:11:54.780 ⇒ 00:12:00.170 Awaish Kumar: In our models, the revenue number is the same in, in Amazon Portal.
115 00:12:01.010 ⇒ 00:12:01.710 Jasmin Multani: Okay.
116 00:12:02.820 ⇒ 00:12:16.529 Jasmin Multani: Maybe I can take that on while Upeth, is working. But basically, we sort of doing, with Jasmine, understand…
117 00:12:17.250 ⇒ 00:12:25.740 Jasmin Multani: the limits to Amazon’s data packaging, and is this related to the SKU stuff that we’ve been seeing?
118 00:12:28.330 ⇒ 00:12:29.979 Jasmin Multani: the SKU industry.
119 00:12:30.370 ⇒ 00:12:36.260 Awaish Kumar: No, no, it’s, it’s kind of a different, in a sense that…
120 00:12:36.390 ⇒ 00:12:40.810 Awaish Kumar: the data we are getting from Polyatomic is
121 00:12:41.270 ⇒ 00:12:45.280 Awaish Kumar: This is not in a way that we usually get, like, in the order table, you get…
122 00:12:45.410 ⇒ 00:12:48.779 Awaish Kumar: For each order, you get the total amount.
123 00:12:49.070 ⇒ 00:13:04.320 Awaish Kumar: refund amount, discounts, everything. It’s not coming in that way. So, for an orders table, there’s nothing, right? There’s no financial information. So I have to grab that from a financial events table, that is something else.
124 00:13:04.460 ⇒ 00:13:10.340 Awaish Kumar: And by using that, I’m trying… So I have, modeled it.
125 00:13:10.700 ⇒ 00:13:15.469 Awaish Kumar: With my understanding that what could be the sales, what are the fee sales, what are the refunds?
126 00:13:15.580 ⇒ 00:13:20.709 Awaish Kumar: But how we are going to put it all together to come up with a number that matches the platform.
127 00:13:21.420 ⇒ 00:13:23.039 Awaish Kumar: That’s what we have to do.
128 00:13:24.060 ⇒ 00:13:28.200 Jasmin Multani: Okay, and that’s, like, another additional ask-for strategy, right?
129 00:13:29.290 ⇒ 00:13:32.669 Awaish Kumar: Yeah, that is the only ask from the strategy right now, is that
130 00:13:33.240 ⇒ 00:13:40.000 Awaish Kumar: model is ready, like, what I need is, you compare the fields in the model, And with the…
131 00:13:40.530 ⇒ 00:13:47.369 Awaish Kumar: with the Amazon platform itself. Like, take an order, compare, and figure out what fields are actually
132 00:13:48.450 ⇒ 00:13:51.839 Awaish Kumar: Aligning with that number, so we can calculate order total.
133 00:13:54.500 ⇒ 00:13:55.120 Jasmin Multani: Okay.
134 00:13:55.400 ⇒ 00:14:04.319 Jasmin Multani: I’ll probably ask, offline how to get access to those Amazon platforms so I can make those QAing.
135 00:14:04.630 ⇒ 00:14:08.380 Awaish Kumar: So, for the Amazon platform, we don’t have access right now.
136 00:14:09.420 ⇒ 00:14:12.270 Awaish Kumar: I and Utam, do have access to their platform.
137 00:14:12.370 ⇒ 00:14:18.280 Awaish Kumar: But that is restricted by permissions. We are not able to actually see the orders.
138 00:14:18.670 ⇒ 00:14:23.210 Awaish Kumar: I have raised it a few times in the client channel, but haven’t received it.
139 00:14:23.330 ⇒ 00:14:27.839 Awaish Kumar: So feel free to make a, like, send a message to Jason.
140 00:14:28.120 ⇒ 00:14:32.069 Awaish Kumar: asking for access to Amazon platform.
141 00:14:34.990 ⇒ 00:14:35.670 Jasmin Multani: Okay.
142 00:14:37.390 ⇒ 00:14:40.589 Jasmin Multani: King Jason, so this today.
143 00:14:41.570 ⇒ 00:14:42.839 Jasmin Multani: Alright, sounds good.
144 00:14:44.140 ⇒ 00:14:47.310 Jasmin Multani: I can focus on that this week.
145 00:14:47.310 ⇒ 00:14:50.230 Awaish Kumar: Then we also finished,
146 00:14:52.440 ⇒ 00:14:57.830 Awaish Kumar: Like, these auto tickets are closed, like, TikTok…
147 00:14:58.410 ⇒ 00:15:02.689 Awaish Kumar: Like, the tickets for the marketing, like,
148 00:15:03.030 ⇒ 00:15:08.090 Awaish Kumar: TikTok, Microsoft, Google, Facebook, and Unified Data Model.
149 00:15:08.380 ⇒ 00:15:09.750 Awaish Kumar: That’s all.
150 00:15:10.560 ⇒ 00:15:11.180 Jasmin Multani: Around.
151 00:15:12.320 ⇒ 00:15:15.330 Jasmin Multani: Can I ask you to, just check these off?
152 00:15:16.220 ⇒ 00:15:17.260 Awaish Kumar: Yeah, I am.
153 00:15:18.420 ⇒ 00:15:20.769 Awaish Kumar: Yeah, yeah, I can do that. I’ll just,
154 00:15:22.550 ⇒ 00:15:25.430 Awaish Kumar: Close them, but yeah, these are all modeling
155 00:15:26.000 ⇒ 00:15:30.710 Awaish Kumar: Tickets needs to go out, and then, We have,
156 00:15:33.130 ⇒ 00:15:39.399 Awaish Kumar: The right… the work that we are working on right now is, for supply chain modeling.
157 00:15:39.650 ⇒ 00:15:40.000 Jasmin Multani: Yeah.
158 00:15:40.000 ⇒ 00:15:53.670 Awaish Kumar: So, it’s for where to go stored. These are two data sources, that we are bringing the data from. I don’t know why you can’t see the tickets here, but they are in, like.
159 00:15:54.510 ⇒ 00:15:57.829 Awaish Kumar: In one of the projects related to supply chain.
160 00:15:58.670 ⇒ 00:15:59.350 Jasmin Multani: Okay.
161 00:15:59.350 ⇒ 00:16:10.370 Awaish Kumar: So, it is where to go stored, and then we have a one called Unify Data Model, which will basically unify these both sources, create a one mod for supply chain.
162 00:16:11.170 ⇒ 00:16:13.260 Awaish Kumar: Yeah, that’s… that’s in progress.
163 00:16:14.210 ⇒ 00:16:24.109 Jasmin Multani: Okay, cool, cool, cool. We’re also finishing up one of our calls, or discovery calls with Supply. So I’m gonna introduce, like, a
164 00:16:24.110 ⇒ 00:16:37.460 Jasmin Multani: journey for them, to validate, and I’ll cross-reference it with your model… data model to make sure, like, hey, the thing that’s… the things that they said were critical for their operations, is that being captured today?
165 00:16:38.680 ⇒ 00:16:45.330 Awaish Kumar: Yeah, so that’s… That’s where we… collaboration comes in. Right now, we are just working in the…
166 00:16:45.570 ⇒ 00:16:46.660 Awaish Kumar: In the dark?
167 00:16:46.910 ⇒ 00:16:52.000 Awaish Kumar: So, whatever we have, trying to create a model based on that, without any requirements.
168 00:16:52.320 ⇒ 00:16:58.650 Awaish Kumar: So, I’m 100% sure that’s not exactly going to land the way you want it.
169 00:16:58.650 ⇒ 00:16:59.190 Jasmin Multani: Yeah.
170 00:16:59.190 ⇒ 00:17:05.820 Awaish Kumar: So, after you… After the discovery, we have some requirements, and then based on that.
171 00:17:05.960 ⇒ 00:17:10.560 Awaish Kumar: We are going to create models from maybe the existing models, so…
172 00:17:10.569 ⇒ 00:17:11.629 Jasmin Multani: Yeah, yeah, I am.
173 00:17:11.630 ⇒ 00:17:12.480 Awaish Kumar: Something like that.
174 00:17:12.480 ⇒ 00:17:15.569 Jasmin Multani: We’re just waiting for the stakeholders to dump all their spreadsheets.
175 00:17:15.579 ⇒ 00:17:16.299 Awaish Kumar: Me too.
176 00:17:16.579 ⇒ 00:17:25.359 Jasmin Multani: But by Friday, I think I’ll do another check-in, because we have a live call with Shivani by Friday.
177 00:17:26.479 ⇒ 00:17:28.509 Jasmin Multani: Okay, cool. Anything else?
178 00:17:30.800 ⇒ 00:17:38.269 Awaish Kumar: No, these are all the tickets that needs… also needs cleanup. I will do it sometime today, but
179 00:17:38.690 ⇒ 00:17:41.839 Awaish Kumar: So, maybe there are some tickets that are not relevant anymore.
180 00:17:42.710 ⇒ 00:17:44.439 Jasmin Multani: All good, all good.
181 00:17:45.700 ⇒ 00:18:02.350 Jasmin Multani: I know this week is gonna be just the priorities pushing out the dashboards, and then next week is queuing the blobby to make sure things are consistent. And also, like, catching whatever spreadsheet issue that they see, and that they escalate, I’ll also see where I can lean in there.
182 00:18:03.460 ⇒ 00:18:08.489 Awaish Kumar: For that issue, I started posting a daily message in Slack.
183 00:18:08.700 ⇒ 00:18:10.950 Awaish Kumar: I… I think you’re able to see that.
184 00:18:11.120 ⇒ 00:18:11.450 Jasmin Multani: Yeah.
185 00:18:12.640 ⇒ 00:18:16.090 Awaish Kumar: So that is, like, these are the missing schools.
186 00:18:16.420 ⇒ 00:18:21.259 Awaish Kumar: that, are not aided to the
187 00:18:21.480 ⇒ 00:18:25.039 Awaish Kumar: The full, like, the report that she’s seen.
188 00:18:25.650 ⇒ 00:18:30.240 Awaish Kumar: So… Yeah, like, she will figure out. If you just add a few, then,
189 00:18:30.780 ⇒ 00:18:34.389 Awaish Kumar: She will again find some screw that is missing, so…
190 00:18:34.580 ⇒ 00:18:38.009 Awaish Kumar: I’ll actually try to compare and come up with all the schools that are missing.
191 00:18:38.780 ⇒ 00:18:43.640 Jasmin Multani: Yeah, I think there are two issues, though. A, those SKUs are missing from the spreadsheet.
192 00:18:43.770 ⇒ 00:18:51.579 Jasmin Multani: and B… When she asks Blobby, there are SKUs that are not being accounted for.
193 00:18:52.800 ⇒ 00:18:55.880 Jasmin Multani: So, those are two separate, platforms.
194 00:18:55.880 ⇒ 00:18:59.810 Awaish Kumar: Yeah, I’m more talking about what she commented on in the Google Sheet.
195 00:18:59.810 ⇒ 00:19:08.539 Jasmin Multani: Okay, yeah, yeah, and I’ll track that. I also gave you, a ticket. That’s gonna impact…
196 00:19:10.000 ⇒ 00:19:16.100 Awaish Kumar: Yeah, I think I saw that it’s, like, renaming some of the metrics in the dbt model, that’s…
197 00:19:17.190 ⇒ 00:19:18.030 Jasmin Multani: Yeah. Yeah.
198 00:19:18.030 ⇒ 00:19:18.929 Awaish Kumar: I’ll do that.
199 00:19:18.930 ⇒ 00:19:36.230 Jasmin Multani: Yeah, yeah, yeah, and then once you’re done, like, I also made it clear, like, how much… what quality check you’re gonna do for DBT, and then once you’re done, send it over to… send the ticket over to me, and then I’ll validate at the spreadsheet level, and then, once I’m done, I’ll validate at the…
200 00:19:36.330 ⇒ 00:19:40.740 Jasmin Multani: Other than I will validate at the Omni level.
201 00:19:40.740 ⇒ 00:19:49.479 Awaish Kumar: Yeah, it needs to be a close collaboration, because it’s… it’s going to break… The Omni dashboards.
202 00:19:49.480 ⇒ 00:20:05.649 Jasmin Multani: Yeah, yeah, yeah, yeah. Just ping us whenever you’re getting started, and when you’re done. Just for, for Garrett and Greg, Shivani keeps finding redundancies, where it’s saying they’re…
203 00:20:06.220 ⇒ 00:20:21.329 Jasmin Multani: everything’s saying POS sales, or there are times when, like, revenue and sales are being used interchangeably. So, this ticket that I’ve cut, like, we’re just gonna go from start to finish and be very robust, like.
204 00:20:21.400 ⇒ 00:20:32.460 Jasmin Multani: sanity check, hey, we’re not using, POS sales redundantly, right? And we’re not conflating revenue with sales, right? At both, like, at each level, like.
205 00:20:32.660 ⇒ 00:20:37.060 Jasmin Multani: dbt, spreadsheet, and omni… omni-channel level.
206 00:20:40.490 ⇒ 00:20:49.879 Greg Stoutenburg: Advait did something like that, for the, for the topic. I mean, sorry, for, somewhere in the semantic layer, right, Advait?
207 00:20:50.520 ⇒ 00:20:51.940 Greg Stoutenburg: So that at least Blobby…
208 00:20:51.940 ⇒ 00:20:53.370 Advait Nandakumar Menon: Yeah, that’s…
209 00:20:53.370 ⇒ 00:20:53.990 Greg Stoutenburg: sake.
210 00:20:54.230 ⇒ 00:20:54.960 Advait Nandakumar Menon: Yeah.
211 00:20:55.700 ⇒ 00:21:13.349 Advait Nandakumar Menon: Yeah, so that’s what I think Ticket 369 or 370, I’m not sure, but one of them, I’m going to make sure that it’s called just point of sale from now, not POS, not POS sales, but yes, that’s one change I’m going to do with respect to topic and AI context in Omni, so… yeah.
212 00:21:13.860 ⇒ 00:21:14.860 Greg Stoutenburg: Yeah, okay.
213 00:21:16.640 ⇒ 00:21:17.789 Jasmin Multani: Okay, cool, cool, cool.
214 00:21:17.890 ⇒ 00:21:25.829 Jasmin Multani: Awesome! And then… No, just send you check what Greg and Garrett have.
215 00:21:26.470 ⇒ 00:21:30.869 Greg Stoutenburg: Mine should look pretty light. Let’s see if, expectation will meet reality here.
216 00:21:31.730 ⇒ 00:21:33.429 Jasmin Multani: Yeah, everything’s done!
217 00:21:33.760 ⇒ 00:21:35.090 Jasmin Multani: Perfect, 100% score.
218 00:21:36.020 ⇒ 00:21:37.990 Greg Stoutenburg: jewel.
219 00:21:38.500 ⇒ 00:21:44.540 Jasmin Multani: Let’s see… Okay, 100%!
220 00:21:44.540 ⇒ 00:21:45.510 Garrett Gibson: Yay.
221 00:21:45.510 ⇒ 00:21:46.180 Greg Stoutenburg: Alright.
222 00:21:47.650 ⇒ 00:21:58.959 Jasmin Multani: Yay! Okay, I will give you one piece of homework, which is the, weekly sheet that I sent over. Maybe I can just bring that up to speed.
223 00:22:00.870 ⇒ 00:22:02.670 Jasmin Multani: Let me pull that up right now.
224 00:22:02.670 ⇒ 00:22:18.659 Garrett Gibson: And so I’m gonna, just to clarify, I’m gonna update the deck again, like, on Wednesday, because I’m trying to keep up with Shivani’s spreadsheet updates, so, I’ll just make sure that I have the deck updated to reflect whatever she modifies in there, to keep it in sync.
225 00:22:20.130 ⇒ 00:22:22.140 Jasmin Multani: Sounds good. Yeah.
226 00:22:22.830 ⇒ 00:22:26.179 Jasmin Multani: Cool, so this is, like, just…
227 00:22:26.180 ⇒ 00:22:33.380 Garrett Gibson: Oh, and actually, probably also on Wednesday, I’ll start up the 4 box, too, because I think I did that too late last week, so I’ll probably just,
228 00:22:33.710 ⇒ 00:22:36.089 Garrett Gibson: Like, start drafting that up on Wednesday.
229 00:22:36.490 ⇒ 00:22:44.599 Jasmin Multani: Yeah, and I’ll also ask people, like, are there, like, very intense call-outs? Like, zero call-outs that they want to offer?
230 00:22:44.820 ⇒ 00:22:46.660 Jasmin Multani: Like, this, I…
231 00:22:46.860 ⇒ 00:22:57.430 Jasmin Multani: I know that you’re leveraging, the spreadsheet and the linear tickets, to get a total picture, but I’m gonna ask each person to provide, like, a…
232 00:22:57.880 ⇒ 00:23:07.490 Jasmin Multani: what is something that’s top of mind that hasn’t been captured yet, that you absolutely want to raise to everyone else.
233 00:23:07.840 ⇒ 00:23:16.439 Garrett Gibson: Yeah, and then those Shivani, like, the new Shivani slides I created, I also kicked those to more of the front of the deck, so that way we’re talking to, like, more of her spreadsheet data.
234 00:23:16.440 ⇒ 00:23:17.090 Jasmin Multani: Yes.
235 00:23:17.090 ⇒ 00:23:21.139 Garrett Gibson: to, like, linear and stuff like that. Yeah, it’s, like, slides 4 and 5.
236 00:23:21.360 ⇒ 00:23:21.930 Jasmin Multani: Yeah, that’s.
237 00:23:21.930 ⇒ 00:23:25.379 Garrett Gibson: Maybe it’s better to go over these slides first, yeah, with her.
238 00:23:26.680 ⇒ 00:23:31.510 Garrett Gibson: I’ll also clean up, like, the text. There’s probably a lot of text and stuff, so maybe I’ll just try to clean that up.
239 00:23:33.440 ⇒ 00:23:39.760 Jasmin Multani: Yeah, no worries. Ideally, This is going to be a very robust, thorough version of the.
240 00:23:39.760 ⇒ 00:23:40.100 Garrett Gibson: Yeah.
241 00:23:40.100 ⇒ 00:23:44.290 Jasmin Multani: And, this is also gonna be a chance for us to be, like.
242 00:23:44.420 ⇒ 00:23:59.119 Jasmin Multani: connecting the dots between each workstream, right? It’s like, where does Awish, need strategy to lead on? Exactly. Awish has asked this from us 3 times in the past 3 weeks, why didn’t we,
243 00:23:59.120 ⇒ 00:24:04.610 Jasmin Multani: let’s figure out, like, why it’s getting dropped, or who it has been with. So,
244 00:24:04.620 ⇒ 00:24:06.889 Jasmin Multani: That’s how I plan on this…
245 00:24:07.200 ⇒ 00:24:19.500 Jasmin Multani: to work, just to have us accountable for our internal working group. Or it’s another way for us to be like, okay, this contract is getting out of hand, we should be asking for more resources here.
246 00:24:20.430 ⇒ 00:24:29.419 Jasmin Multani: No, I’m not done cleaning this up yet, but more to come, and then I’ll send it over to Garrett to manage. If you’re willing to manage this, Garrett.
247 00:24:30.060 ⇒ 00:24:31.999 Garrett Gibson: Yeah, no, I can help out with that, no worries.
248 00:24:32.830 ⇒ 00:24:33.830 Jasmin Multani: Awesome, thanks.
249 00:24:35.490 ⇒ 00:24:39.630 Jasmin Multani: Are there any other call-outs, or things people want to voice?
250 00:24:42.620 ⇒ 00:24:46.170 Greg Stoutenburg: Not for me. Advait, how’s your workload across your clients?
251 00:24:47.100 ⇒ 00:24:58.520 Advait Nandakumar Menon: So right now I’m working on the default that BDR, the dashboard, which we have been chatting in the morning and afternoon. So my plan is to…
252 00:24:58.760 ⇒ 00:25:09.549 Advait Nandakumar Menon: work on that a little, and then handle these tickets in Element as well, and then switch back to finishing up the BDR dashboard and
253 00:25:10.060 ⇒ 00:25:25.949 Advait Nandakumar Menon: maybe address the feedback on customer enablement and reporting, but parallel, I also have to work on the dashboard feedback that Jasmine has given the tickets for, so that’s my current workload. It’s manageable, if that’s what you’re asking.
254 00:25:25.950 ⇒ 00:25:30.240 Greg Stoutenburg: Yes, that’s… okay, great. That’s the main thing. Cool, just wanted to make sure.
255 00:25:30.380 ⇒ 00:25:33.309 Greg Stoutenburg: I know I’m throwing tons of stuff at them across clients, so…
256 00:25:33.310 ⇒ 00:25:34.639 Advait Nandakumar Menon: Yeah, yeah.
257 00:25:35.250 ⇒ 00:25:36.190 Advait Nandakumar Menon: Appreciate it.
258 00:25:36.190 ⇒ 00:25:38.600 Jasmin Multani: If you want to spend, like.
259 00:25:38.780 ⇒ 00:25:44.529 Jasmin Multani: I know you only have 4 dashboards, but if you want to spend, like, 2 days per dashboard, let me
260 00:25:45.430 ⇒ 00:25:50.639 Jasmin Multani: And then we can voice it over. And I’ll just give Shivani other things to QA.
261 00:25:51.280 ⇒ 00:25:52.140 Advait Nandakumar Menon: Okay, yeah.
262 00:25:52.140 ⇒ 00:25:58.750 Jasmin Multani: But there are plenty of other things that I can find for her to QA and, like, discuss, especially on the supply chain side. So.
263 00:25:58.750 ⇒ 00:25:59.650 Advait Nandakumar Menon: Yep, nope.
264 00:26:00.240 ⇒ 00:26:04.650 Jasmin Multani: Yeah. I’ll touch base with you again later today to see if we can…
265 00:26:05.210 ⇒ 00:26:13.500 Jasmin Multani: show that dashboard to Shivani that you had completed, but I’m gonna wait for you to edit the capitalizations and stuff.
266 00:26:13.500 ⇒ 00:26:14.290 Advait Nandakumar Menon: No.
267 00:26:14.290 ⇒ 00:26:14.870 Jasmin Multani: foresh.
268 00:26:14.870 ⇒ 00:26:15.460 Advait Nandakumar Menon: Yep.
269 00:26:15.810 ⇒ 00:26:17.290 Advait Nandakumar Menon: Yep, sounds good.
270 00:26:17.290 ⇒ 00:26:20.689 Jasmin Multani: Sounds good! Alright, I’ll give you guys 2 minutes back then.
271 00:26:21.880 ⇒ 00:26:22.810 Greg Stoutenburg: That’s all. Fix this.
272 00:26:22.810 ⇒ 00:26:24.599 Advait Nandakumar Menon: See you guys. Bye. Bye.